Nature-Inspired Computing: Concepts, Methodologies, Tools, and Applications

Nature-Inspired Computing: Concepts, Methodologies, Tools, and Applications

Information Resources Management Association

Copyright: © 2017 |Pages: 1780

ISBN13: 9781522507888|ISBN10: 1522507884|EISBN13: 9781522507895

DOI: 10.4018/978-1-5225-0788-8

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Management Association, Information Resources, editor. Nature-Inspired Computing: Concepts, Methodologies, Tools, and Applications. IGI Global, 2017. https://doi.org/10.4018/978-1-5225-0788-8

APA

Management Association, I. (Ed.). (2017). Nature-Inspired Computing: Concepts, Methodologies, Tools, and Applications. IGI Global. https://doi.org/10.4018/978-1-5225-0788-8

Chicago

Management Association, Information Resources, ed. Nature-Inspired Computing: Concepts, Methodologies, Tools, and Applications. Hershey, PA: IGI Global, 2017. https://doi.org/10.4018/978-1-5225-0788-8

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As technology continues to become more sophisticated, mimicking natural processes and phenomena also becomes more of a reality. Continued research in the field of natural computing enables an understanding of the world around us, in addition to opportunities for man-made computing to mirror the natural processes and systems that have existed for centuries.

Nature-Inspired Computing: Concepts, Methodologies, Tools, and Applications takes an interdisciplinary approach to the topic of natural computing, including emerging technologies being developed for the purpose of simulating natural phenomena, applications across industries, and the future outlook of biologically and nature-inspired technologies. Emphasizing critical research in a comprehensive multi-volume set, this publication is designed for use by IT professionals, researchers, and graduate students studying intelligent computing.

Table of Contents

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Front Materials

Title Page

Copyright Page

Editorial Advisory Board

Preface

Chapters

Fundamental Concepts and Theories

Chapter 1

A Theoretical Framework for Parallel Implementation of Deep Higher Order Neural Networks (pages 1-11)

Shuxiang Xu, Yunling Liu

This chapter proposes a theoretical framework for parallel implementation of Deep Higher Order Neural Networks (HONNs). First, we develop a new partitioning approach for mapping HONNs to individual computers within a master-slave...

Chapter 2

An Exploration of Backpropagation Numerical Algorithms in Modeling US Exchange Rates (pages 12-27)

Salim Lahmiri

This chapter applies the Backpropagation Neural Network (BPNN) trained with different numerical algorithms and technical analysis indicators as inputs to forecast daily US/Canada, US/Euro, US/Japan, US/Korea, US/Swiss, and US/UK...

Chapter 3

Image Representation, Filtering, and Natural Computing in a Multivalued Quantum System (pages 28-56)

Sanjay Chakraborty, Lopamudra Dey

Image processing on quantum platform is a hot topic for researchers now a day. Inspired from the idea of quantum physics, researchers are trying to shift their focus from classical image processing towards quantum image processing....

Chapter 4

Some Properties on the Capability of Associative Memory for Higher Order Neural Networks (pages 57-86)

Hiromi Miyajima, Shuji Yatsuki, Noritaka Shigei, Hirofumi Miyajima

Higher order neural networks (HONNs) have been proposed as new systems. In this paper, we show some theoretical results of associative capability of HONNs. As one of them, memory capacity of HONNs is much larger than one of the...

Chapter 5

Swarm Intelligence in Solving Bio-Inspired Computing Problems: Reviews, Perspectives, and Challenges (pages 87-110)

Debi Prasanna Acharjya, Ahmed P. Kauser

Currently, a huge amount of data is available across various domains including biological data. Classification of these data, clustering, and data analysis is tedious and has become popular in recent research. In particular...

Chapter 6

Evolutionary Algorithms: Concepts, Designs, and Applications in Bioinformatics (pages 111-137)

Ka-Chun Wong

Inspired from nature, evolutionary algorithms have been proven effective and unique in different real world applications. Comparing to traditional algorithms, its parallel search capability and stochastic nature enable it to excel in...

Chapter 7

Artificial Neural Network and Its Application in Steel Industry (pages 138-171)

Itishree Mohanty, Dabashish Bhattacherjee

The recent developments in computational intelligence has enhances the applicability of empirical modelling in different areas particularly in the area of machine learning. These new approaches are based on analysing the data about a...

Chapter 8

Parallel Multi-Criterion Genetic Algorithms: Review and Comprehensive Study (pages 172-186)

Bhabani Shankar Prasad Mishra, Subhashree Mishra, Sudhansu Sekhar Singh

The objective of this paper is to study the existing and current research on parallel multi-objective genetic algorithms (PMOGAs) through an intensive experiment. Many early efforts on parallelizing multi-objective genetic algorithms...

Chapter 9

Evolutionary Computing to Examine Variation in Proteins with Evolution (pages 187-202)

Sujay Ray

Amino-acid sequences play a pivotal role for the structure of proteins. Alterations in a single amino-acid may vary the protein functioning. Alignment of sequences recognizes evolutionary and structurally related residues in a group...

Chapter 10

Diagnosis of Breast Cancer Using Intelligent Information Systems Techniques (pages 203-214)

Ahmad Al-Khasawneh

Breast cancer is the second leading cause of cancer deaths in women worldwide. Early diagnosis of this illness can increase the chances of long-term survival of cancerous patients. To help in this aid, computerized breast cancer...

Chapter 11

On Mutual Relations amongst Evolutionary Algorithm Dynamics and Its Hidden Complex Network Structures: An Overview and Recent Advances (pages 215-239)

Ivan Zelinka

In this chapter, we do synthesis of three partially different areas of research: complex networks, evolutionary computation and deterministic chaos. Ideas, results and methodologies reported and mentioned here are based on our...

Development and Design Methodologies

Chapter 12

Artificial Higher Order Neural Network Models (pages 241-311)

Ming Zhang

This chapter introduces the background of HONN model developing history and overview 24 applied artificial higher order neural network models. This chapter provides 24 HONN models and uses a single uniform HONN architecture for ALL...

Chapter 13

An Intelligent Process Development Using Fusion of Genetic Algorithm with Fuzzy Logic (pages 312-348)

Kunjal Bharatkumar Mankad

Intelligent System (IS) can be defined as the system that incorporates intelligence into applications being handled by machines. The chapter extensively discusses the role of Genetic Algorithm (GA) in the search and optimization...

Chapter 14

Developmental Swarm Intelligence: Developmental Learning Perspective of Swarm Intelligence Algorithms (pages 349-367)

Yuhui Shi

In this article, the necessity of having developmental learning embedded in a swarm intelligence algorithm is confirmed by briefly considering brain evolution, brain development, brainstorming process, etc. Several swarm intelligence...

Chapter 15

Neural Network Models: Usefulness and Limitations (pages 368-395)

Eliano Pessa

The Artificial Neural Network (ANN) models gained a wide popularity owing to a number of claimed advantages such as biological plausibility, tolerance with respect to errors or noise in the input data, learning ability allowing an...

Chapter 16

Derivation and Simulation of an Efficient QoS Scheme in MANET through Optimised Messaging Based on ABCO Using QualNet (pages 396-425)

Abhijit Das, Atal Chaudhuri

Mobile Ad hoc Network or MANET is a collection of heterogeneous mobile nodes and is infrastructure-less by choice or by default. MANET is prone to confront a lot of challenges in designing a proper Quality of Service (QoS) model...

Chapter 17

A Method for Classification Using Data Mining Technique for Diabetes: A Study of Health Care Information System (pages 426-449)

Ahmad Al-Khasawneh

Many researchers in the health information system field have been attracted to develop computer applications that help in the diagnosis process. Imperatively, data mining algorithms address the vital role in all of these...

Chapter 18

Hookes-Jeeves-Based Variant of Memetic Algorithm (pages 450-475)

Dipti Singh, Kusum Deep

Due to their wide applicability and easy implementation, Genetic algorithms (GAs) are preferred to solve many optimization problems over other techniques. When a local search (LS) has been included in Genetic algorithms, it is known...

Chapter 19

An Artificial Neural Network Model as the Decision Support System of Ports (pages 476-499)

Can Elmar Balas

The new feasibility analysis model proposed in this study for coastal projects consists of three interrelated decision support models: 1) Artificial Neural Network (ANN) to determine the rates and capacity of cargo by considering the...

Chapter 20

Innovative Hierarchical Fuzzy Logic for Modelling Using Evolutionary Algorithms (pages 500-527)

M. Mohammadian, R. J. Stonier

This paper considers issues in the design and construction of a fuzzy logic system to model complex (nonlinear) systems. Several important applications are considered and methods for the decomposition of complex systems into...

Chapter 21

A Black-Box Model for Estimation of the Induction Machine Parameters Based on Stochastic Algorithms (pages 528-552)

Julien Maitre, Sébastien Gaboury, Bruno Bouchard, Abdenour Bouzouane

Knowledge on asynchronous machine parameters (resistances, inductances…) has become necessary for the manufacturing industry in the interest of optimizing performances in a production system (roll-to-roll processing, wind...

Chapter 22

Adaptive Hybrid Higher Order Neural Networks for Prediction of Stock Market Behavior (pages 553-570)

Sarat Chandra Nayak, Bijan Bihari Misra, Himansu Sekhar Behera

This chapter presents two higher order neural networks (HONN) for efficient prediction of stock market behavior. The models include Pi-Sigma, and Sigma-Pi higher order neural network models. Along with the traditional gradient...

Chapter 23

Genetic Algorithms for Small Enterprises Default Prediction: Empirical Evidence from Italy (pages 571-607)

Niccolò Gordini

Company default prediction is a widely studied topic as it has a significant impact on banks and firms. Moreover, nowadays, due to the global financial crisis, there is a need to use even more advanced methods (such as soft computing...

Tools and Technologies

Chapter 24

Quantum Computing Based Technique for Cancer Disease Detection System (pages 609-629)

Setu Kumar Chaturvedi, Milan Jain

Barring any cancer prevention breakthroughs, the expansion of the aged population will likely increase number of older individuals diagnosed for cancer in the coming decades. Dimensions of the cancer burden and its devastating manner...

Chapter 25

MEMS Microrobot with Pulse-Type Hardware Neural Networks Integrated Circuit (pages 630-647)

Ken Saito, Minami Takato, Yoshifumi Sekine, Fumio Uchikoba

Hexapod locomotive Micro-Electro Mechanical Systems (MEMS) microrobot with Pulse-type Hardware Neural Networks (P-HNN) locomotion controlling system is presented in this chapter. MEMS microrobot is less than 5 mm width, length, and...

Chapter 26

Ultra High Frequency Polynomial and Trigonometric Higher Order Neural Networks for Control Signal Generator (pages 648-681)

Ming Zhang

This chapter develops a new nonlinear model, Ultra high frequency Polynomial and Trigonometric Higher Order Neural Networks (UPT-HONN), for control signal generator. UPT-HONN includes UPS-HONN (Ultra high frequency Polynomial and...

Chapter 27

Ultra High Frequency Sigmoid and Trigonometric Higher Order Neural Networks for Data Pattern Recognition (pages 682-715)

Ming Zhang

This chapter develops a new nonlinear model, Ultra high frequency siGmoid and Trigonometric Higher Order Neural Networks (UGT-HONN), for data pattern recognition. UGT-HONN includes Ultra high frequency siGmoid and Sine function...

Chapter 28

Artificial Sine and Cosine Trigonometric Higher Order Neural Networks for Financial Data Prediction (pages 716-744)

Ming Zhang

This chapter develops two new nonlinear artificial higher order neural network models. They are Sine and Sine Higher Order Neural Networks (SIN-HONN) and Cosine and Cosine Higher Order Neural Networks (COS-HONN). Financial data...

Chapter 29

Cosine and Sigmoid Higher Order Neural Networks for Data Simulations (pages 745-760)

Ming Zhang

New open box and nonlinear model of Cosine and Sigmoid Higher Order Neural Network (CS-HONN) is presented in this paper. A new learning algorithm for CS-HONN is also developed from this study. A time series data simulation and...

Chapter 30

Higher Order Neural Network for Financial Modeling and Simulation (pages 761-788)

Partha Sarathi Mishra, Satchidananda Dehuri

Financial market creates a complex and ever changing environment in which population of investors are competing for profit. Predicting the future for financial gain is a difficult and challenging task, however at the same time it is...

Chapter 31

Ultra High Frequency SINC and Trigonometric Higher Order Neural Networks for Data Classification (pages 789-829)

Ming Zhang

This chapter develops a new nonlinear model, Ultra high frequency SINC and Trigonometric Higher Order Neural Networks (UNT-HONN), for Data Classification. UNT-HONN includes Ultra high frequency siNc and Sine Higher Order Neural...

Chapter 32

Swarm Intelligence for Biometric Feature Optimization (pages 830-863)

Santosh Kumar, Deepanwita Datta, Sanjay Kumar Singh

Swarm Intelligence (SI) and bio-inspired computation has gathered great attention in research in the last few years. Numerous SI-based optimization algorithms have gained huge popularity to solve the complex combinatorial...

Chapter 33

Particle Swarm Optimization Algorithm as a Tool for Profiling from Predictive Data Mining Models (pages 864-892)

Goran Klepac

This chapter introduces the methodology of particle swarm optimization algorithm usage as a tool for finding customer profiles based on a previously developed predictive model that predicts events like selection of some products or...

Chapter 34

Quantum Behaved Swarm Intelligent Techniques for Image Analysis: A Detailed Survey (pages 893-931)

Sandip Dey, Siddhartha Bhattacharyya, Ujjwal Maulik

In this chapter, an exhaustive survey of quantum behaved techniques on swarm intelligent is presented. The techniques have been categorized into different classes, and in conclusion, a comparison is made according to the benefits of...

Chapter 35

Navigation Control of a Mobile Robot under Time Constraint using Genetic Algorithms, CSP Techniques, and Fuzzy Logic (pages 932-954)

Tlijani Hayet, Tlijani Hatem, Knani Jilani

This chapter proposes a two-input-and-one-output fuzzy controller for a two-wheeled mobile robot. The robot moves following a hybrid plan based on Genetic Algorithms and Constraint Satisfaction Problem techniques. The path yielded by...

Utilization and Application

Chapter 36

A Survey on Swarm Robotics (pages 956-998)

Ying Tan

In this chapter, the current work on swarm robotics is briefly reviewed. Swarm robotics, inspired from nature swarm, is a combination of swarm intelligence and robotic, and shows great potential in several aspects. Firstly of all...

Chapter 37

Using a Hybrid System Composed of Neural Networks and Genetic Algorithms for Financial Forecasting (pages 999-1007)

Mihaela Dumitrescu

The possibility of applying artificial neural networks in different areas determined the discovery of more complex structures. This chapter describes the characteristic aspects of using a back-propagation neural network algorithm in...

Chapter 38

Analytics on Fireworks Algorithm Solving Problems with Shifts in the Decision Space and Objective Space (pages 1008-1038)

Shi Cheng, Quande Qin, Junfeng Chen, Yuhui Shi, Qingyu Zhang

Fireworks algorithms for solving problems with the optima shift in decision space and/or objective space are analyzed in this paper. The standard benchmark problems have several weaknesses in the research of swarm intelligence...

Chapter 39

Studies of Computational Intelligence Based on the Behaviour of Cockroaches (pages 1039-1086)

Amartya Neogi

In this chapter, the author expands the notion of computational intelligence using the behavior of cockroaches. An introduction to cockroach as swarm intelligence emerging research area and literature review of its growing concept is...

Chapter 40

Application of Genetic Algorithms in Inventory Control (pages 1087-1098)

Vinod Kumar Mishra

The genetic algorithm (GA) is an adaptive heuristic search procedures based on the mechanics of natural selection and natural genetics. Inventory control is widely used in the area of mathematical sciences, management sciences;...

Chapter 41

Utilizing Feature Selection on Higher Order Neural Networks (pages 1099-1114)

Zongyuan Zhao, Shuxiang Xu, Byeong Ho Kang, Mir Md Jahangir Kabir, Yunling Liu, Rainer Wasinger

Artificial Neural Network has shown its impressive ability on many real world problems such as pattern recognition, classification and function approximation. An extension of ANN, higher order neural network (HONN), improves...

Chapter 42

On the Accelerated Convergence of Genetic Algorithm Using GPU Parallel Operations (pages 1115-1130)

Cheng-Chieh Li, Jung-Chun Liu, Chu-Hsing Lin, Winston Lo

The genetic algorithm plays a very important role in many areas of applications. In this research, the authors propose to accelerate the evolution speed of the genetic algorithm by parallel computing, and optimize parallel genetic...

Chapter 43

Multi-Objective Generation Scheduling Using Genetic-Based Fuzzy Mathematical Programming Technique (pages 1131-1160)

Abdellah Derghal, Noureddine Goléa

This chapter presents a solution for multi-objective Optimal Power Flow (OPF) problem via a genetic fuzzy formulation algorithm (GA-FMOPF). The OPF problem is formulated as a multiple objective problem subject to physical...

Chapter 44

Comparative Analysis of Statistical, Machine Learning, and Grey Methods for Short-Term Electricity Load Forecasting (pages 1161-1183)

Tuncay Ozcan, Tarik Küçükdeniz, Funda Hatice Sezgin

Electricity load forecasting is crucial for electricity generation companies, distributors and other electricity market participants. In this study, several forecasting techniques are applied to time series modeling and forecasting...

Chapter 45

Evaluation of Genetic Algorithm as Learning System in Rigid Space Interpretation (pages 1184-1228)

Bhupesh Kumar Singh

Genetic Algorithm (GA) (a structured framework of metaheauristics) has been used in various tasks such as search optimization and machine learning. Theoretically, there should be sound framework for genetic algorithms which can...

Chapter 46

Application of Artificial Intelligence Techniques to Handle the Uncertainty in the Chemical Process for Environmental Protection (pages 1229-1260)

Tianxing Cai

In the chemical process, the uncertainties are always encountered. Therefore, the algorithm of process modeling, simulation, optimization, and control should have the capability to handle the uncertain parameter. Meta-Heuristics...

Chapter 47

Application of Biologically Inspired Techniques for Industrial and Environmental Research via Air Quality Monitoring Network (pages 1261-1288)

Tianxing Cai

Industrial and environmental research will always involve the study of the cause-effect relationship between the emissions and the surrounding environment. Qualitative and mixed methods researchers have employed a variety of...

Chapter 48

Comparative Analysis of Neural Network and Fuzzy Logic Techniques in Credit Risk Evaluation (pages 1289-1305)

Asogbon Mojisola Grace, Samuel Oluwarotimi Williams

Credit risk evaluation techniques that aid effective decisions in credit lending are of great importance to the financial and banking industries. Such techniques assist credit managers to minimize the risks often associated with...

Chapter 49

Using Self Organizing Maps for Banking Oversight: The Case of Spanish Savings Banks (pages 1306-1332)

Felix Lopez-Iturriaga, Iván Pastor-Sanz

This chapter combines two methods based on neural networks (trait recognition and self-organizing maps) to develop a model of bankruptcy prediction. The authors apply the method to the Spanish savings banks, most of them rescued by...

Chapter 50

Application of Genetic Algorithm and Back Propagation Neural Network for Effective Personalize Web Search-Based on Clustered Query Sessions (pages 1333-1352)

Suruchi Chawla

In this paper novel method is proposed using hybrid of Genetic Algorithm (GA) and Back Propagation (BP) Artificial Neural Network (ANN) for learning of classification of user queries to cluster for effective Personalized Web Search....

Issues and Challenges

Chapter 51

Role of Consumer Engagement and Swarm Intelligence in Management of a Brand at Social Media (pages 1354-1370)

Rajshree Singh

The traditional media has its own place and will always be there but the revolution in marketing era will change the thinking of the society as a whole and the various communication channels will always be in flux. The ability to...

Chapter 52

Parameter Optimization of Photovoltaic Solar Cell and Panel Using Genetic Algorithms Strategy (pages 1371-1390)

Benmessaoud Mohammed Tarik, Fatima Zohra Zerhouni, Amine Boudghene Stambouli, Mustapha Tioursi, Aouad M'harer

In this chapter, we propose to perform a numerical technique based on genetic algorithms (GAs) to identify the electrical parameters (Is, Iph, Rs, Rsh, and n) of photovoltaic (PV) solar cells and modules. The one diode type approach...

Chapter 53

Customer Profiling in Complex Analytical Environments Using Swarm Intelligence Algorithms (pages 1391-1422)

Goran Klepac

Customer profiling is always an interesting task from perspective of business. It became even bigger challenge in situation of complex analytical environment. Complex analytical environment can be caused by multiple modality of...

Chapter 54

Stochastic Drought Forecasting Exploration for Water Resources Management in the Upper Tana River Basin, Kenya (pages 1423-1455)

Raphael M. Wambua, Benedict M. Mutua, James M. Raude

This chapter presents the trend of drought as a stochastic natural disaster influenced by the climate variability for the upper Tana River basin in Kenya. Drought frequency, duration and intensity in the upper Tana River basin have...

Chapter 55

Theoretical Analyses of the Universal Approximation Capability of a Class of Higher Order Neural Networks Based on Approximate Identity (pages 1456-1470)

Saeed Panahian Fard, Zarita Zainuddin

One of the most important problems in the theory of approximation functions by means of neural networks is universal approximation capability of neural networks. In this study, we investigate the theoretical analyses of the universal...

Chapter 56

AI-Based Cyber Defense for More Secure Cyberspace (pages 1471-1489)

Dimitar Stevo Bogatinov, Mitko Bogdanoski, Slavko Angelevski

The growing network attacks and intrusions have put the government organizations at a great risk. In cyberspace, humans have great limitations in data analyze and cyber defense because of the amount of data they have to process and...

Chapter 57

Hybrid BFO and PSO Swarm Intelligence Approach for Biometric Feature Optimization (pages 1490-1518)

Santosh Kumar, Sanjay Kumar Singh

Nature-inspired novel swarm intelligence algorithms have gained more proliferation due to a variety of applications and uses in optimization of complex problems and selection of discriminatory sets of features to classify huge...

Chapter 58

From Optimization to Clustering: A Swarm Intelligence Approach (pages 1519-1544)

Megha Vora, T. T. Mirnalinee

In the past two decades, Swarm Intelligence (SI)-based optimization techniques have drawn the attention of many researchers for finding an efficient solution to optimization problems. Swarm intelligence techniques are characterized...

Chapter 59

Potential Indicators Based Neural Networks for Cash Forecasting of an ATM (pages 1545-1563)

Partha Sarathi Mishra, Satchidananda Dehuri

Cash forecasting is one of the important tasks in the domain of computational finance. A number of tools have been developed by various groups of researchers and are being used by banks or corporate to identify future cash needs....

Chapter 60

Swarm Intelligence for Dimensionality Reduction: How to Improve the Non-Negative Matrix Factorization with Nature-Inspired Optimization Methods (pages 1564-1589)

Andreas Janecek, Ying Tan

Low-rank approximations allow for compact representations of data with reduced storage and runtime requirements and reduced redundancy and noise. The Non-Negative Matrix Factorization (NMF) is a special low-rank approximation that...

Chapter 61

Determination of Bearing Capacity of Shallow Foundation Using Soft Computing (pages 1590-1626)

Jagan J., Swaptik Chowdhury, Pratik Goyal, Pijush Samui, Yıldırım Dalkiliç

The ultimate bearing capacity is an important criterion for the successful implementation of any geotechnical projects. This chapter studies the feasibility of employing Gaussian process regression (GPR), Extreme learning machine...

Emerging Trends

Chapter 62

Green Computing and Its Impact (pages 1628-1642)

Shailendra Singh, Sunita Gond

The mission “Saving Earth” has become need of all of us to sustain life on the earth. There are many holistic approaches for Green Computing which impact on stack holders of the computing system including hardware, software and...

Chapter 63

Schematic Classification Model of Green Computing Approaches (pages 1643-1650)

Nishtha Kesswani, Shelendra Kumar Jain

Every electronic device has an impact on the environment, and computing devices are not an exception. Green computing is a highly motivated smart computing which tries to save energy and environment by minimizing harmful impacts of...

Chapter 64

Prediction of International Stock Markets Based on Hybrid Intelligent Systems (pages 1651-1667)

Salim Lahmiri

This paper compares the accuracy of three hybrid intelligent systems in forecasting ten international stock market indices; namely the CAC40, DAX, FTSE, Hang Seng, KOSPI, NASDAQ, NIKKEI, S&P500, Taiwan stock market price index, and...

Chapter 65

Green and Energy-Efficient Computing Architecture for E-Learning (pages 1668-1692)

K. Palanivel, S. Kuppuswami

Information and Communication Technology (ICT) is one of the fast growing industries that facilitate many latest services to the users and therefore, the number of users is increasing rapidly. The usage of ICT and its life cycle...

Chapter 66

Adoption of Virtualization in Cloud Computing: A Foundation Step towards Green Computing (pages 1693-1700)

Nusratullah Khan, Asadulah Shah, Kajal Nusratullah

There has been rapid expansion of the information technology due to contribution to emission of carbon dioxide. The cloud computing technology has been perceived to present solution to various studies that try to investigate on the...

Chapter 67

Toward a Sustainable Fishery Management Policy: An Artificial Neural Network Model for Predicting Bull Shark (Carcharhinus Leucas) Presence (pages 1701-1722)

Steven P. Coy, Margaret F. Shipley, J. Brooke Shipley-Lozano

This article proposes an Artificial Neural Network (ANN) model to predict neonatal and juvenile bull shark habitat usage in the Sabine Pass, located within the Gulf of Mexico between Louisiana and Texas. Given continuing discussion...

Chapter 68

The Contribution of Teleworking towards a Green Computing Environment (pages 1723-1738)

Iheanyi Chuku Egbuta, Brychan Thomas, Said Al-Hasan

The aims of the chapter are to consider the strategic green issues of teleworking in terms of the environment, transport, location, office space, and resource use for modern organisations and business sectors and to formulate a...

Chapter 69

New Genetic Operator (Jump Crossover) for the Traveling Salesman Problem (pages 1739-1752)

Hicham El Hassani, Said Benkachcha, Jamal Benhra

Inspired by nature, genetic algorithms (GA) are among the greatest meta-heuristics optimization methods that have proved their effectiveness to conventional NP-hard problems, especially the traveling salesman problem (TSP) which is...

Chapter 70

Improving Performance of Higher Order Neural Network using Artificial Chemical Reaction Optimization: A Case Study on Stock Market Forecasting (pages 1753-1780)

Sarat Chandra Nayak, Bijan Bihari Misra, Himansu Sekhar Behera

Multilayer neural networks are commonly and frequently used technique for mapping complex nonlinear input-output relationship. However, they add more computational cost due to structural complexity in architecture. This chapter...

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